Development Plans

Constraints

Two popular approaches for constraint handling are active-set and interior point methods. The APOPT solver uses an active-set method while the BPOPT solver uses an interior point method.

Detection of Infeasibility

For mixed-integer problems, an NLP solver that can quickly solve from a nearby solution or eliminate infeasible points is critical for overall convergence. A focus area in APOPT solver development is in detection of sub-optimal or infeasible solutions.

Parallel Computing

The best solvers are designed to exploit the abilities of multi-core computer architectures. With increasingly parallelized architectures, a solver must exploit these resources.

Source Code for Solver Development

APOPT maintains a development environment for mixed integer nonlinear programming (MINLP) solvers in MATLAB. The solvers are written in both a higher level programming language (MATLAB) and as an efficient compiled version (C++/Fortran). The development platform aids the testing of exploratory algorithms and techniques.